Who says we can't share?

This page will serve as a collection of resources for myself and others to use freely. Use the notes at your own risk, no promises that they're error-free or comprehensible to anyone but myself. 😀

Social Media Stuff

Research that focuses on various aspects of social media. For the most part, misinformation, disinformation, social bots, bot detection, and similarly related topics.

  • Bakshy, Messing, Adamic (2015) - Exposure to ideologically diverse news and opinion on Facebook
  • Bollen, Mao, Zeng (2020) - Twitter mood predicts the stock market
  • Creski (2020) - A Decade of Social Bot Detection
  • Del Vicario, Bessi, Zollo, Petroni, Scala, Caldarelli, Stanley, and Quattrociocchi (2016) - The spreading of misinformation online
  • Deutch (2020) - Tracking Facebook’s Election Misinformation "Super-Spreaders" (NewsGuard Special Report: Election Misinformation)
  • Ferrara, Chang, Chen, Muric, Patel - Characterizing social media manipulation in the 2020 U.S. presidential election
  • Ferrara, Varol, Davis, Menczer, Flammini (2016) - The rise of social bots
  • Grinberg, Joseph, Friedland, Swire-Thompson, Lazer (2019) - Fake news on Twitter during the 2016 U.S. presidential election
  • Kramer, Guillory, Hancock (2014) - Experimental evidence of massive-scale emotional contagion through social networks
  • Pei, Muchnik, Andrade Jr., Zheng, & Makse (2014) - Searching for superspreaders of information in real-world social media
  • Shao, Ciampaglio, Varol, Yang, Flammini, Menczer (2018) - The spread of low-credibility content by social bots
  • Vosoughi, Roy, Aral (2018) - The spread of true and false news online
  • Random Course Readings

    These links are to notes on various literature encountered through my Ph.D. program at IU.

  • Barthelemy (2014) - Scaling: lost in the smog
  • Bernstein, Shore, Lazer (2018) - How intermittent breaks in interaction improve collective intelligence
  • Bishop (2020) - How Scientists Can Stop Fooling Themselves Over Statistics
  • Butts (2009) - Revisiting the Foundations of Network Analysis
  • Christakis and Fowler (2010) - Social Network Sensors for Early Detection of Contagious Outbreaks
  • Cristelli, Tacchela & Pietronero (2015) - The Heterogeneous Dynamics of Economic Complexity
  • De Solla Price (1965) - Networks of Scientific Papers
  • Domingos (2012) - A Few Useful Things to Know About Machine Learning
  • Flake (1998) - The Computational Beauty of Nature: Computer Explorations of Fractals, Chaos, Complex Systems and Adaptation (pp. 1-8; 129-136)
  • Helbing, Farkas, Vicsek (2000) - Simulating dynamical features of escape panic
  • Kitsak, Gallos, Havlin, Liljeros, Muchnik, Stanley, Makse (2010) - Identification of influential spreaders in complex networks
  • Makse, Havlin & Stanley (1995) - Modeling Urban Growth Patterns
  • Mantegna & Stanley (1995) - Scaling Behaviour in the Dynamics of an Economic Index
  • Miller and Page (2009) - Complex Adaptive Systems: Computational Models of Social Life (Ch3: pp. 35-43)
  • Miller and Page (2009) - Complex Adaptive Systems: Computational Models of Social Life (Ch5: pp. 57-77)
  • McIntyre (2019) - The Scientific Attitude: Defending Science from Denial, Fraud, and Pseudoscience. (Intro & Ch. 1)
  • Néda, Ravasz, Brecht, Vicsek & Barabási (2000) - The sound of many hands clapping
  • Page - The Model Thinker: What You Need to Know to Make Data Work for You (Ch2: pp. 13-25)
  • Radicchi, Fortunato, and Castellano (2008) - Universality of Citation Distributions: Toward an objective measure of scientific impact
  • Salganik et al. (2020) - Measuring the predictability of life outcomes with a scientific mass collaboration
  • Siever (1968) - Science: Observational, Experimental, Historical
  • Song, Qu, Blumm, Barabasi (2010) - Limits of Predictability in Human Mobility
  • Stanley et al. (1996) - Scaling behaviour in the growth of companies
  • Weaver (1948) - Science and Complexity
  • Winsberg (2019) - Computer Simulations in Science
  • Complex Systems

    This is a collection of single slide summaries that I (or others) presented for i709 Complex Systems on various topics.
    You'll also find longer-form powerpoint presentations from when I was responsible for leading a presentation with another student.

  • DeVerna (2020) - Economic Complexity (overview of a few papers)
  • DeVerna (2020) - Generalized h-Index (Science of Science)
  • DeVerna (2020) - Mobility Prediction and Travel Distance (Mobility)
  • DeVerna (2020) - Modeling the Collective Motion of Escape Panic (Collective Motion)
  • Aiyappa (2020) - Power Laws
  • DeVerna (2020) - Scaling Laws and Mechanistic Insight (Science of Cities)
  • DeVerna (2020) - Why Linear Regression and Power Law Distributions Don't Mix (Power Laws)
  • Example Code

    Random collection of my own code which I think is interesting.

  • Creating Fractals via the method of Iterated Maps
  • Rough Compound Interest
  • Funding

    Some helpful links to student funding resources.

  • Undergraduate scholarships and tips on applying
  • Graduate fellowships and tips on applying
  • Misc.

    Other random things that might be useful in the future.

  • How to Read a Book v5.0 - Paul N. Edwards